John R Schomburg

Title: John R. Schomburg: Innovator in Data Processing Technologies

Introduction

John R. Schomburg is a notable inventor based in New Brighton, MN (US). He has made significant contributions to the field of data processing, holding a total of 2 patents. His work focuses on enhancing the efficiency and accuracy of computational processes.

Latest Patents

Schomburg's latest patents include an "Apparatus for performing quadratic convergence division in a large data" and an "Apparatus for creating a multiplication pipeline of arbitrary size." The first patent describes a binary division circuit designed for large data processing systems. This circuit performs division with both floating and fixed-point numbers, utilizing a modified multiplier unit to achieve higher precision calculations. The design incorporates an augmented multiplier circuit combined with a quotient correction technique, allowing for faster division operations compared to traditional methods.

The second patent outlines a multiply pipeline with a parity circuit, which serves as a building block in a multiplication pipeline of arbitrary size. This invention includes circuits for generating and checking parity, ensuring the detection of single-bit errors in the multiplication circuitry. The proposed design features a 6-bit by 6-bit multiply chip and a 6-bit by 4-bit adder/register chip, both of which work together to enhance the reliability and efficiency of multiplication processes.

Career Highlights

John R. Schomburg is associated with Sperry Corporation, where he has contributed to various innovative projects. His expertise in data processing technologies has positioned him as a valuable asset within the company.

Collaborations

One of his notable coworkers is Louis B. Bushard, with whom he has likely collaborated on various projects within Sperry Corporation.

Conclusion

John R. Schomburg's contributions to data processing technologies through his patents demonstrate his innovative spirit and technical expertise. His work continues to influence advancements in computational efficiency and accuracy.